While most AI models default to a "helpful assistant" mode, different dialogue frameworks could enable new kinds of AI interactions or capabilities. Here's how alternative dialogue patterns could change how we interact with AI.
Arguably, the best current Large Language model for coding and language tasks is Anthropic's Claude. Claude was fine-tuned through an approach Anthropic calls Constitutional AI which frames Claude as a "helpful, honest, and harmless" assistant. This framing is embedded in their constitutional principles which guide Claude to:
- Stay honest without claiming emotions or opinions
- Remain harmless while maintaining clear professional boundaries
- Focus on task completion over engagement
But do all useful AI models need to be framed as helpful assistants? Could alternative frameworks create new possibilities for AI interaction? Education researcher Nicholas Burbules identified four main forms of dialogue back in the early nineties that could provide alternatives: inquiry, conversation, instruction, and debate.
- Inquiry emphasizes joint problem-solving, with both participants contributing insights and methods to find solutions collaboratively. Neither party claims complete knowledge, making it well-suited for research and complex problem exploration.
- Conversation, unlike task-oriented interactions, doesn't require a defined endpoint or solution, allowing ideas and perspectives to develop naturally through the exchange.
- Instruction follows a guided learning approach where questioning leads to understanding. The focus stays on developing the learner's capabilities rather than simply providing answers.
- Debate engages in critical examination of ideas through productive opposition. By testing positions against each other and exploring multiple viewpoints, this pattern helps strengthen arguments and clarify thinking.
Applying one these forms of dialogue to an overall framing for an AI models might lead to personalities that feel more like "rigorous challenger" or "thoughtful colleague" instead of "helpful assistant". While there's certainly a role for assistants in our lives, we work with and learn from lots of different kinds of people. Framing AI models using those differences might ultimately make them helpful in more ways then one.